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  4. Vol 7, Issue 9, 2023

A study on vegetable commodity replenishment considering single item quantity limitations—based on gray prediction and linear regression modeling

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DOI: 10.23977/acss.2023.070916 | Downloads: 7 | Views: 315

Author(s)

Doudou Zhang 1, Xuemei Xiang 1, Jinyi Yang 1

Affiliation(s)

1 Bussiness College, Southwest University, Chongqing, 402460, China

Corresponding Author

Doudou Zhang

ABSTRACT

Data elements are beginning to play an important role in the selling of vegetable items in supermarkets. In order to get the best pricing and replenishment strategy under the limitation of the number of vegetable items, this paper firstly calculates the profit contribution rate of each item and sorts out the top 33 available items, and prioritizes the items with the top profit contribution rate for replenishment. Finally, a linear programming model is developed to solve the pricing strategy for maximizing the revenue of the superstore under the constraints of display quantity and weight of individual products.

KEYWORDS

GM(1,1) Model, Linear Programming, Pricing Strategy, Replenishment Strategy

CITE THIS PAPER

Doudou Zhang, Xuemei Xiang, Jinyi Yang, A study on vegetable commodity replenishment considering single item quantity limitations—based on gray prediction and linear regression modeling. Advances in Computer, Signals and Systems (2023) Vol. 7: 121-129. DOI: http://dx.doi.org/10.23977/acss.2023.070916.

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